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Found 10 papers, 1 papers with code
Deep Reinforcement Learning for Solving Management Problems: Towards A Large Management Mode
We introduce a deep reinforcement learning (DRL) approach for solving management problems including inventory management, dynamic pricing, and recommendation.
RiskMiner: Discovering Formulaic Alphas via Risk Seeking Monte Carlo Tree Search
Existing alpha mining only employs the neural network agent, unable to utilize the structural information of the solution space.
NID-SLAM: Neural Implicit Representation-based RGB-D SLAM in dynamic environments
In this paper we present NID-SLAM, which significantly improves the performance of neural SLAM in dynamic environments.
A New Weighted Food CPI from Scanner Big Data in China
Scanner big data has potential to construct Consumer Price Index (CPI).
RED: A Systematic Real-Time Scheduling Approach for Robotic Environmental Dynamics
This process ensures the scheduling framework's compatibility with MIMONet and maximizes efficiency.
Deep learning radiomics for assessment of gastroesophageal varices in people with compensated advanced chronic liver disease
Validation analysis revealed that the AUCs of DLRP were 0. 91 for GEV (95% CI 0. 90 to 0. 93, p < 0. 05) and 0. 88 for HRV (95% CI 0. 86 to 0. 89, p < 0. 01), which were significantly and robustly better than canonical risk indicators, including the value of LSM and SSM.
Predicting China's CPI by Scanner Big Data
Scanner big data has potential to construct Consumer Price Index (CPI).
ArtCoder: An End-to-End Method for Generating Scanning-Robust Stylized QR Codes
Quick Response (QR) code is one of the most worldwide used two-dimensional codes.
An End-to-end Method for Producing Scanning-robust Stylized QR Codes
Quick Response (QR) code is one of the most worldwide used two-dimensional codes.~Traditional QR codes appear as random collections of black-and-white modules that lack visual semantics and aesthetic elements, which inspires the recent works to beautify the appearances of QR codes.
A New Unified Deep Learning Approach with Decomposition-Reconstruction-Ensemble Framework for Time Series Forecasting
A new variational mode decomposition (VMD) based deep learning approach is proposed in this paper for time series forecasting problem.
